Journal article 156 views 48 downloads
Clinical perspectives on AI integration: assessing readiness and training needs among healthcare practitioners
Journal of Decision Systems, Volume: 34, Issue: 1
Swansea University Authors:
Tinotenda Masawi, Edward Miller, Daniel Rees , Roderick Thomas
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© 2025 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0).
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DOI (Published version): 10.1080/12460125.2025.2458874
Abstract
The rapid advancement of Artificial Intelligence (AI) is transforming healthcare, offering both opportunities and challenges. This study examines the perceptions of healthcare practitioners in Wales regarding AI’s role in diagnostics. Through semi-structured interviews with 10 expert practitioners f...
Published in: | Journal of Decision Systems |
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ISSN: | 1246-0125 2116-7052 |
Published: |
Informa UK Limited
2025
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Online Access: |
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URI: | https://cronfa.swan.ac.uk/Record/cronfa68743 |
Abstract: |
The rapid advancement of Artificial Intelligence (AI) is transforming healthcare, offering both opportunities and challenges. This study examines the perceptions of healthcare practitioners in Wales regarding AI’s role in diagnostics. Through semi-structured interviews with 10 expert practitioners from various specializations, it uncovers diverse views shaped by experience and second-hand knowledge. While AI is recognized for enhancing diagnostic accuracy and administrative efficiency, concerns persist about the loss of human touch, data security, and biases. A key finding is the unanimous call for comprehensive AI training to bridge knowledge gaps and build confidence. Using an interpretivist qualitative approach, with purposive sampling and thematic analysis, the study highlights nuanced practitioner perspectives. The findings underscore the need for equitable AI resource distribution and tailored training to address geographical disparities. The study advocates for future research with larger, more diverse samples and follow-up evaluations to assess AI training’s long-term impact on healthcare practice. |
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Keywords: |
Artificial intelligence; innovation; healthcare; clinician; information systems; UTAUT |
College: |
Faculty of Humanities and Social Sciences |
Funders: |
Swansea University |
Issue: |
1 |